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2019-02

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cc-by (c) Clavería González, Óscar , 2019
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/129623

Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations

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https://doi.org/10.1186/s12651-019-0253-4

Abstract

This study aims to refine unemployment forecasts by incorporating the degree of consensus in consumers' expectations. With this objective, we first model the unemployment rate in eight European countries using the step-wise algorithm proposed by Hyndman and Khandakar (J Stat Softw 27(3):1-22, 2008). The selected optimal autoregressive integrated moving average (ARIMA) models are then used to generate out-of-sample recursive forecasts of the unemployment rates, which are used as benchmark. Finally, we replicate the forecasting experiment including as predictors both an indicator of unemployment, based on the degree of agreement in consumer unemployment expectations, and a measure of disagreement based on the dispersion of expectations. In both cases, we obtain an improvement in forecast accuracy in most countries. These results reveal that the degree of agreement in consumers' expectations contains useful information to predict unemployment rates, especially for the detection of turning points.

Subject

Atur, Conducta dels consumidors, Enquestes de consum, Anàlisi de regressió, Indicadors econòmics

Subject (English)

Unemployment, Consumer behavior, Consumer surveys, Regression analysis, Economic indicators

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Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

Citation

CLAVERÍA GONZÁLEZ, Óscar. Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations. Journal for Labour Market Research. 2019. Vol. 53, num. 3, pags. 1-10. ISSN 2510-5019. [consulted: 9 of August of 2026]. Available at: https://hdl.handle.net/2445/129623

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